Widespread use or misuse of antibiotics has spurred evolutionarily adaptations that enable bacteria to survive many of our most powerful drugs. While existing antimicrobials are losing their effect, there has been in recent years a steep decline in the development of new drugs. If this trend continues, the drugs we have to combat resistant microorganisms will soon be depleted. The growing incidence of illness and death caused by antibiotic resistant infections, coupled with the cost that society has to pay for them, reflect our urgent need for new antibiotics that either block or circumvent resistance mechanisms, or attack new targets. We need a better understanding of the different ways in which resistance develops so that we can develop new methods to identify and counteract it. The research proposed here will provide a broader picture of the evolution of resistance and dissect the genetic mechanisms of its development. We plan to conduct laboratory evolution experiments in which we adapt E. coli to antibiotics from three commonly used classes and discern the mechanisms by which they develop resistance using high-throughput sequencing and whole genome linkage analysis. Once contributing loci are identified and validated, we will use global epistasis assays and transcriptome analysis to place them in the broader network context of specific signaling and regulatory pathways. We will classify these mutations in order to help simplify and untangle the magnitude and complexity of antibiotic-bacterial dynamics. Previous research suggests that clinical levels of antibiotic resistance may develop through the sequential accumulation of mutations of small individual effect. Understanding the order in which different mutations occur will give us information that may be useful for developing better diagnostics and in delaying the development of resistance. Throughout this research, special attention will be paid to the trajectory of resistance in the face of increasing drug dosage and also to associated fitness costs to the microorganism under other conditions. The ability of microbes to resist antibiotics often negatively impacts their fitness in the absence of treatment; however, mutations that confer resistance are often quickly followed by additional mutations elsewhere in the genome that compensate for these costs. Understanding the order in which different mutations occur will give us information about how strains become increasingly resistant. Also, since the fitness costs determine the strength of selection against resistant bacteria, analysis of these costs may inform novel treatment regimens. The aim of this research is to uncover new targets to combat resistance, new pathways that synergize with a particular antibiotic and, more broadly, to strengthen and enrich the underlying principles that will lay the foundation for the next generation of novel therapies, drug discovery, and diagnostics in the field.